MARKETING EVOLUTION
constraints. Pulling that data together into a unified environment that properly reflects the business is what ultimately enables meaningful AI use cases. Once that foundation exists, organisations can layer models from OpenAI, Anthropic, Google or others on top of the data and begin extracting value from information they already have.
I think of it as every business – especially in financial services – is sitting on a mountain of gold. That gold is their data. But before it can create value, it has to be mined and refined. Or, in this case, structured and contextualised.
The other thing happening right now is that many organisations believe the greater risk is being late to AI rather than being wrong. That’ s creating enormous pressure to move quickly, even when the underlying data foundations aren’ t fully in place.
AI may provide some value initially, but organisations will see diminishing returns if the infrastructure isn’ t there to support it.
Q. WHAT’ S THE‘ INTERMEDIARY GAP’ COSTING MARKETERS IN BANKING AND INSURANCE ATTRIBUTION?
» There’ s significant cost, but it’ s recoverable. At the end of the day, marketers optimise what they can measure. Often, that means they over invest in the wrong things and under invest in what they can’ t properly attribute – especially upper – funnel and brand activity that happens well before conversion.
That challenge becomes especially pronounced in financial services because conversion is often owned by intermediaries: brokers, branches, advisors, platforms or other downstream stakeholders. Marketing may be driving demand, but the transaction is frequently captured elsewhere in the system.
As a result, attribution tends to credit the closer rather than the creator of demand. It’ s an age – old measurement problem, but it becomes amplified in industries where customer journeys are longer, more fragmented and distributed across stakeholders.
To solve for this, that information must be pulled together holistically,
86 July 2026